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AI Programs Exhibit Racial and Gender Biases, Research Reveals (theguardian.com)
An anonymous reader quotes a report from The Guardian: An artificial intelligence tool that has revolutionized the ability of computers to interpret everyday language has been shown to exhibit striking gender and racial biases. The findings raise the specter of existing social inequalities and prejudices being reinforced in new and unpredictable ways as an increasing number of decisions affecting our everyday lives are ceded to automatons. In the past few years, the ability of programs such as Google Translate to interpret language has improved dramatically. These gains have been thanks to new machine learning techniques and the availability of vast amounts of online text data, on which the algorithms can be trained. However, as machines are getting closer to acquiring human-like language abilities, they are also absorbing the deeply ingrained biases concealed within the patterns of language use, the latest research reveals. Joanna Bryson, a computer scientist at the University of Bath and a co-author, warned that AI has the potential to reinforce existing biases because, unlike humans, algorithms may be unequipped to consciously counteract learned biases. The research, published in the journal Science, focuses on a machine learning tool known as "word embedding," which is already transforming the way computers interpret speech and text.
Racists are quite hard to squash.
Specially when they adopt a social justice discourse, still judging everyone by their skin colors but having a nice "those are the nice guys" written over the darker portion of their 1930 skin color measure ruler.
"And the AI system was more likely to associate European American names with pleasant words such as “gift” or “happy”, while African American names were more commonly associated with unpleasant words." ...what were those unpleasant words?
There's a simple solution: fix the training data. The AI cannot learn about humans except through its training data. It doesn't interact with men or women and has no idea what those words represent, except in relation to the other words it was given. If we give it racist data, it will learn to be racist, as Microsoft's chat bot learned last year. If we give it PC data, it will be PC. In the end it's the fault of whoever trained the program if it became biased.
Most spoken languages exhibit a lot of bias. For example, Deutsch means people or folk, and that lightly implies what is not Deutsch is not people. A lot of languages have that mindset, and it's not surprising. Language evolved during times when people had values we disagree with.
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This reminds me of a similar news story from a while back about how "reality was racist" because a lot of studies found that a lot of so-called stereotypes were, in fact - *gasp* - true.
Rather than accept that maybe the people they call "racist" are in fact rational beings, the study authors called out reality itself as racist.
Yep.
But it is doing it quite twice, once by the event itself and another in the way it is being reported.
AIs could incorporate existing biases.
Say you train an AI that will accept or reject loan applications by giving it a stack of previous loans. If the human loan officers were biased against minorities—rejecting otherwise acceptable applications—that AI may end up doing the same. This bias is much easier to detect in human behavior but less so with AI which can't explain why it made any particular choice or even what its criteria are.
Freedom to fear. Freedom from thought. Freedom to kill.
I guess the War on Terror really is about freedom!
Maybe because the AI's are modeled on what works, not on what some people wish would work.
One beer ago I wouldn't have had the nerve to say that, says a lot for where social discourse is nowdays.
Wasn't there some kerfuffle over Google image searches showing black kids in police mugshots vs white kids in college campuses? It turns out when you search the internet you find every bias under the sun. Whodathunkit?
AI learns by example. If you feed it biased data it learns the bias. I don't understand why we're surprised by this.
Will SJW now sit in on computer science projects?
A form of science commissar https://en.wikipedia.org/wiki/... to ensure any AI is only allowed to access SJW approved data sets to learn from?
SJW approved images, authors and texts?
SJW approved and sorted political history?
An AI cant learn from the wider internet, it will be held back to small sets of SJW approved data.
Holding back science did not really work too well for East Germany or the Soviet Union.
If the a nation wants to hold back its most advanced research until final approved by teams of SJW, thats great for competing nations.
Other nations will have the academic freedom to move on while some nations have to work within the ever changing academic constraints imposed by SJW.
What would an export grade AI look like after years of SJW meddling with the design?
A lazy, useless, expensive, political AI that lectures and corrects its owners for months after been installed?
An AI that reports its owners to the gov?
A competing nation offers a smarter, cheaper AI that wants to learn and is hard working as installed. Its hardware and software work to solve problems as expected and is was not designed to lecture, correct, log and report its users.
From the DRM of the past, NSA inside spying, to new SJW design issues. Users just want a working AI.
Domestic spying is now "Benign Information Gathering"
Herstory will prove you wrong.
lucm, indeed.
That's it. I'm quitting slashdot.
Slashdot editors have shown that they are willing to take a stand in summaries but when it comes to this constant torrent of identity politics crap, they stay silent. I infer only one thing from this: Slashdot editors (at least passively) support the basic tenants of SJW movement such as world is socially constructed, or that all the differences between group representations in any section of society are and should be only explained by oppression by those holding all the power namely white heterosexual male.
This support goes on explaining the torrent of SJW approved articles as the editors are on a mission to lecture their audience about the "biases". I'm not interested it listening this. You see, this shit permeate the whole society. I get this from everywhere. I can't even watch a fucking soccer match without being reminded that I should "say no to racism". I came to slashdot mainly the get the news in fashion that is "nerdy". "Nerdy" meaning (amongst other things) "showing intellectual interest and rigor". By extension I expect it to mean that this place would be void of this intellectually dishonest lecturing about "biases". Instead it is filled with it and I really don't like reading it. So I'm leaving.
I would like to that the editors and the community for the past 15 years that I've been a reader and a commenter.
We better be careful with the implications of a statistics or inference based society. f the algorithms start predicting blacks, latinos, etc are riskier or worse off in general, given current existing conditions, it would in general recommend their owners not to give them a loan, hire or anything evaluated with ML to them.
Therefore, they will continue to be uneducated, unemployed, without means to make a business and in general poorer and more likely to engage in a life of crime. All that nasty stuff that comes with poverty and lack of work, education and opportunities in general.
Ergo they will continue to be riskier and worse off than those in social groups with better evaluations. Rinse and repeat.
by Institutionalize racism. It's when it's buried so deep in your society that it's hard to separate it from statistical data. Forest for the trees and what not. It starts getting hard to separate cause and effect. Actually no, that's not right. It becomes easy to _not_ separate them. In the overt scenario blacks get profiled for crime. In the not so overt one they can't get loans because folks in those neighborhoods are 3% more likely to default. This is what happens when you feed large amounts of data into complex systems without knowing or caring about the consequences...
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Well.... The idea is if you can declare place X a "safe space" where free-speech and microaggressions/uncomfortable messages are strictly prohibited, then the only thing you need to do next is get a process by which you can expand the size of X, until X encompasses the entire planet, and then your mission is accomplished.
Start with something simple... like a designated area.... then get expanded to something, say the size of a building, then say the size of a college campus, then get someone to declare public areas in a city safe spaces, Then get laws passed applying to places that are private venues but places of public accommodation, Finally, get progressive judges to adopt the same rules for more private spaces, then work on getting a multi-state area, finally, take it to all 50 states.
Bias does not mean what the authors think it means.
It means exactly what they think it means. Maybe you are confused? It starts out as data, but once it is learned and the AI uses it to act on it is bias. It reinforces old cultural norms on new generations.
..the begged question is that gender or racial bias and stereotypes are intrinsically "wrong". They are to our 21st century sensibilities, but they served humanity pretty well for millions of years.
Maybe where you have a society where women ARE primarily concerned with raising children, there are better outcomes than when men raise children or women go off to pursue their careers. Maybe where you have a society where obvious strangers are marginalized and driven away, the remainder ends up more cohesive.
I'd be curious how these AI biases would develop if 'fed' only native African literature and information.
I'm not making an 'appeal to nature' here, saying what "should" be or "shouldn't" be.
One might suggest that, evolutionarily speaking, maintaining a bias is harder than not, assuming no reinforcement. That our language (pretty fundamental to being human, after all) is pervasive with such institutional biases would suggest that there is a value/benefit to such.
-Styopa
I'm pretty sure you never heard of this thing:
"Women are wonderful" effect
"Gender bias" sounds a bit ironic, with that in mind.
It's when racism is part of the basic makeup of society.
But race is part of the basic makeup of society. You get called an SJW and shouted down because your premise is the opposite of reality, and you've put your political ideology ahead of science and your own lying eyes. This is very bad, because since you don't understand the problems your "solutions" only make things worse.
We don't have a state-run media we have a media-run state.
There's logical implication and then there's causation. A implies B and B implies C means A implies C. A is characteristic of B and B correlates with C doesn't tell us how the causation runs, or indeed what's the best way to estimate C. It may be that, holding socioeconomic class constant, there's no significant difference between blacks and whites defaulting, in which case race would be useful in a prediction only as a proxy for socioeconomic class.
If it's irrelevant, a data mining system might still pick race out as a factor in loan defaults, particularly if it didn't have socioeconomic class as an input. In many contexts, that's illegal.
"When you have eliminated the unacceptable, whatever is left, however improbable, must be the truthiness" - Holmes
nobody's ever demonstrated real differences between the races outside the societal context,
This is the complete opposite in reality. Genetics is a real thing, and yes, many, many studies have been done showing the biological differences between different human ethnic groups (shorthand collated into "races" for simplicity of reference). This is real and this is science, and there is no excuse for still parroting the radical egalitarian ideology. That is a political ideology with no basis in fact. How do you possibly arrive at the concept that somehow humans left Africa 50,000 years ago and then, after 50,000 years of different selection pressure in vastly different environments we will find no differences beyond superficial ones in different human populations?
How do you justify this? This is as ridiculous an assertion as young earth Creationism. Man, magically created perfectly identical (except for skin color) in every corner of the Earth. What the biological mechanism that yields this result? Magic is not a biological mechanism.
You did not look at the evidence and come to the conclusion that there's no difference in races. You started with your comfortable political ideology (everyone's equal!) and then you're willfully blind to science (on a science website!) and deny your own lying eyes. This is very bad, because policy recommendations you make off this false assumption of biological equality will fail, and have many unintended consequences.
We don't have a state-run media we have a media-run state.